💰 LocalBudgetAI

A modern, local-first personal finance dashboard with privacy at its core.

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📚 Table of Contents

• ✨ Key Features
• 📸 Screenshots
• 🎥 Demo Video
• 🚀 Getting Started
• 🧠 How the AI Works
• 🛠️ Tech Stack
• 🛡️ Privacy & Security
• 📂 Folder Structure
• 🤝 Contributing
• 📄 License
• 🙏 Acknowledgements

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✨ Key Features

• 📊 Interactive Dashboards: Create stunning, interactive financial dashboards with Plotly. Hover for details, zoom into trends, and export charts with a single click.
• 🗓️ Financial Analytics: Get a clear view of your finances with monthly and category-wise breakdowns of income, expenses, and savings.
• 🤖 Natural Language AI Assistant: Chat with your data using a powerful, dual-LLM AI assistant powered by Ollama (Mistral & Llama3). Ask complex questions and get instant insights.
• 💸 Budget Optimization: Receive AI-driven advice on optimizing your budget, setting financial goals, and understanding your spending behavior.
• 🔒 Works Fully Offline: Your data is stored locally in a SQLite database. The app works perfectly without an internet connection.
• 🔐 100% Data Privacy: No cloud servers, no data leaks. All processing happens on your machine, ensuring your financial information remains completely private.

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📸 Screenshots

 

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🎥 Demo Video

Check out the demo video to see LocalBudgetAI in action!

Note: The demo video is located at DEMO/DEMO-VID(V1).mp4

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🚀 Getting Started

Prerequisites

• Python 3.8+
• pip (Python package manager)
• An IDE (e.g., VS Code)

1. Clone the Repository

git clone https://www.github.com/MananVyas01/LocalBudgetAI.git
cd LocalBudgetAI

2. Set Up a Virtual Environment

Create and activate a virtual environment to keep dependencies isolated.

# For macOS/Linux
python3 -m venv venv
source venv/bin/activate

# For Windows
python -m venv venv
.\venv\Scripts\activate

3. Install Dependencies

Install all required packages from the requirements.txt file.

pip install -r requirements.txt

4. Run the App

Launch the Streamlit application.

streamlit run app/main.py

5. Set Up Local AI Features

To enable the AI assistant, you need to install Ollama and pull the required models.

1. Install Ollama: Follow the official instructions at ollama.ai.
2. Pull Models: Open your terminal and run the following commands:

   ollama pull mistral
   ollama pull llama3

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🧠 How the AI Works

LocalBudgetAI uses a sophisticated dual-LLM system via Ollama to provide intelligent financial insights.

• 🤖 Dual LLMs: The app leverages both Mistral and Llama3 models. If one model fails or provides a poor response, the system automatically retries with the other, ensuring reliability.
• 🎯 Intent Recognition: The AI is trained to understand financial queries, recognize user intent, and provide context-aware answers based on your data.
• 📈 Predictive Analytics: The AI can analyze historical data to forecast spending trends and help you plan for future financial goals.

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🛠️ Tech Stack

• Backend: Python
• Frontend: Streamlit
• Database: SQLite
• Data Manipulation: Pandas, NumPy
• Visualizations: Plotly
• AI/NLP: Ollama, NLTK, TextBlob
• Machine Learning: Scikit-learn

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🛡️ Privacy & Security

• 🔒 100% Local Data: Your financial data is stored in a local SQLite database and is never sent to the cloud.
• ✈️ Offline Mode: The app is fully functional without an internet connection.
• 🚫 No Third-Party Sharing: We respect your privacy. Your data is never shared with any third parties.

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📂 Folder Structure

LocalBudgetAI/
│
├── app/
│   ├── main.py             # Main Streamlit application
│   ├── database.py         # Database connection and queries
│   ├── analyzer.py         # Core data analysis functions
│   ├── plotly_analyzer.py  # Plotly visualization functions
│   ├── llm_helper.py       # Helper for basic AI functionalities
│   └── advanced_llm_helper.py # Helper for advanced AI features
│
├── data/
│   ├── expenses.db         # SQLite database
│   └── README.md
│
├── DEMO/
│   ├── AI-Assistant.png
│   ├── Analytics.png
│   ├── Main-Dashboard.png
│   └── DEMO-VID(V1).mp4
│
├── requirements.txt        # Project dependencies
└── README.md               # This file

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🤝 Contributing

Contributions are welcome! Please feel free to submit a pull request or open an issue to discuss your ideas.

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📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

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🙏 Acknowledgements

• Streamlit for the amazing web framework.
• Ollama for making local AI accessible.
• Plotly for the beautiful and interactive charts.